A Continuum of Play-Based Learning: The Role of the Teacher in Play-Based Pedagogy and the Fear of Hijacking Play
Bibliographic record
Abstract
Research Findings: Research has demonstrated the developmental and educational benefits of play. Despite these benefits, teacher-directed academic instruction is prominent in kindergarten. There is increasing acknowledgment in curricula and policies of the challenges presented by a lack of play in classrooms and the need to support academic learning using developmentally appropriate practices. Current research emphasizes a narrow definition of play-based learning as a child-directed practice, resulting in teacher uncertainty about the implementation of this pedagogical approach. Fifteen kindergarten classrooms were examined using qualitative methodology, including observations and teacher interviews. Two different teacher profiles emerged: The 1st profile saw play and learning as separate constructs and reported challenges meeting academic demands using play-based learning. Their students primarily engaged in free play. The 2nd profile believed that play could support academic learning and that teachers fill an important role in play. Their students engaged in 5 different types of play, situated along a continuum from child directed to more teacher directed. Practice or Policy: The continuum of play-based learning provides a broader and more concrete definition of play-based learning to help teachers implement this pedagogical approach and to enhance the study of play-based learning in early years research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.049 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".